文章基本信息

标题：Application of PID optimization control strategy based on particle swarm optimization (PSO) for battery charging system
本地全文：下载
作者：Wu, Tiezhou ; Zhou, Cuicui ; Yan, Zhe 等
期刊名称：Intl Jnl of Low-Carbon Technologies
印刷版ISSN：1748-1317
电子版ISSN：1748-1325
出版年度：2020
卷号：15
期号：4
页码：528-535
DOI：10.1093/ijlct/ctaa020
出版社：Oxford University Press
摘要：The battery charging process has nonlinear and hysteresis properties. PID (Proportion Integration Differentiation) control is a conventional control method used in the battery charging process. The control effect is determined by the PID control parameters ${K}_p$ , ${K}_i$ and ${K}_d$ ⁠ . The traditional PID parameter setting method is difficult to give the appropriate parameters, which affects the battery charging efficiency. In this paper, the particle swarm optimization (PSO) is used to optimize the PID parameters. Aiming at the defects of basic PSO, such as slow convergence speed, low convergence precision and easy to be premature, a modified particle swarm optimization algorithm is proposed, and the optimized PID parameters are applied to the battery charging control system. Also, the experimental results show that the battery charging process possesses better dynamic performance and the charging efficiency of the battery has increased from 86.44% to 91.47%, and the charging temperature rise has dropped by 1°C.
关键词：battery;PID parameters;particle swarm optimization